We propose three benchmarks based on TEACh sessions to study the ability of learned models to achieve aspects of embodied intelligence: Execution from Dialog History (EDH), Trajectory from Dialog (TfD) and Two-Agent Task Completion (TATC).
We also demonstrate baseline performance on these benchmarks.
To model the Follower agent for the EDH and TfD benchmarks, we build on the Episodic Transformer (E.T.) model [1]}
as a baseline.
When modeling both agents for end-to-end task completion, we demonstrate the difficulty of engineering rule-based solvers.
